Flink ProcessWindowFunction 和WindowFunction使用

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已于 2022-02-10 14:33:05 修改

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文章标签： flink 大数据 big data

于 2022-02-10 14:21:32 首次发布

本文链接：https://blog.youkuaiyun.com/Y_FC_EMBEDD/article/details/122859234

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本文介绍了在Flink中遇到的两个错误：一是由于keyBy()算子使用方式导致的类型不匹配问题，二是WindowFunction导入错误。通过更正keyBy()的类型参数和选用正确的WindowFunction导入路径，成功解决了这些问题。总结了Flink 1.14.3版本中keyBy()的使用方法和推荐使用ProcessWindowFunction的原因。

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错误提示一：

overloaded method value aggregate with alternatives:
  [ACC, V, R](preAggregator: org.apache.flink.api.common.functions.AggregateFunction[org.example.hot.items.UserBehavior,ACC,V], windowFunction: org.apache.flink.streaming.api.scala.function.ProcessWindowFunction[V,R,org.apache.flink.api.java.tuple.Tuple,org.apache.flink.streaming.api.windowing.windows.TimeWindow])(implicit evidence$13: org.apache.flink.api.common.typeinfo.TypeInformation[ACC], implicit evidence$14: org.apache.flink.api.common.typeinfo.TypeInformation[V], implicit evidence$15: org.apache.flink.api.common.typeinfo.TypeInformation[R])org.apache.flink.streaming.api.scala.DataStream[R] <and>
  [ACC, V, R](preAggregator: org.apache.flink.api.common.functions.AggregateFunction[org.example.hot.items.UserBehavior,ACC,V], windowFunction: (org.apache.flink.api.java.tuple.Tuple, org.apache.flink.streaming.api.windowing.windows.TimeWindow, Iterable[V], org.apache.flink.util.Collector[R]) => Unit)(implicit evidence$10: org.apache.flink.api.common.typeinfo.TypeInformation[ACC], implicit evidence$11: org.apache.flink.api.common.typeinfo.TypeInformation[V], implicit evidence$12: org.apache.flink.api.common.typeinfo.TypeInformation[R])org.apache.flink.streaming.api.scala.DataStream[R] <and>
  [ACC, V, R](preAggregator: org.apache.flink.api.common.functions.AggregateFunction[org.example.hot.items.UserBehavior,ACC,V], windowFunction: org.apache.flink.streaming.api.scala.function.WindowFunction[V,R,org.apache.flink.api.java.tuple.Tuple,org.apache.flink.streaming.api.windowing.windows.TimeWindow])(implicit evidence$7: org.apache.flink.api.common.typeinfo.

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